Sweet dreams

Fool yourself

According to CSA’s Hélène Pielmeier, LSPs often complain of struggling to get visibility and brand recognition and have their marketing and sales efforts meet targets. Really? With all those sales and marketing experts crowding the industry? Obviously, signaling is wrong, despite the experts, or maybe because of them, since sales and marketing are still the lion’s share in hiring.

On the other hand, no LSP has the resources to build a brand and presence similar to that ofany of today’s giants, and Pielmeier’s advice looks like just another do-it-yourself suggestion from a marketing-for-dummies book.

In fact, identifying target market segments is a toiling task for any typical do-everything-in-every-language LSP whose highly predictable expectation is indeed for ultra-specialized ultra-cheap helpless vendors, to deal with any possible request from any possible customer.

It is no coincidence that most LSPs share accesso to the same vendors, especially when highly experienced and educated, but usually go for vendors of proven availability rather than with positive and verified capabilities. And it does not matter whether they are skilled and reliable, even though the subject matter is challenging and possibly sensitive.

Likewise, if you ask any LSP about its experience with translator training, this LSP will indulge in endless complaints about how newly graduates are so unskilled, especially technologically, only to discover that the same LSP is possibly still worse. Indeed, the same LSP would be happy to host some interns, obviously unpaid, who must however provide the same productivity as experienced translators, from the very beginning. The keyword, then, is ‘cheap labor’ as the only way to keep profiting from ever narrowing margins, thus avoiding investments that, inevitably, would force them to give up their boats, their luxury cars, and moderate their passion for fashion outfits, golfing, Cuban cigars, fine wine, etc. Mind you, there’s nothing wrong with fine wine, cigars or garment, even when one smells like spirits, wears muddy shoes, hasn’t long visited any hairdresser, but can’t stop talking of fashion shows and driving ranges, playing high society.

Selling translation is a hard task; selling translation in a vertical market is the hardest of all: You have to know the subject, the market, the challenges, the players and their needs and demands. You cannot improvise. It takes time to plan and implement market research, devise a marketing strategy and a focused campaign. All this takes money, hard money not just pennies.

This is one of the reasons why consolidation is a recurring trend: The only way to secure your own market share, access others, and possibly expand your offering and gain some weight is through M&As.

Getting back to Hélène Pielmeier’s advice, would a trade magazine in any other industry ever publish an article by an unrecognized player from a minor industry, however interesting as a potential supplier? You should pay for it, provided the editor and the publisher accept paid inserts.

Actually, CSA is following Hélène Pielmeier’s advice: It is targeting LSPs through trade publications and industry events, and its brand is now largely recognizable, in the translation industry. Of course, things are easier when you have two or three competitors rather than a few hundreds.

So what?

Hélène Pielmeier’s advice is not exactly wrong. It is a classic: It looks like common sense, practical, and straightforward. Unfortunately, it is a little belated, and the companies willing to follow it would be even more belated.

Differentiation and diversification have been discussed for a while now, together with business models and practices and their obsolescence and inefficiency. Both differentiation and diversification require a major effort in any established business. Specifically, developing a matchless unique selling proposition (USP) is the easiest way to stand out from competition. Unfortunately, things are not that simple. In fact, the entire industry has one USP—quality —and this is a way to be and remain undifferentiated.

Also, the typical business model of the translation industry has proven obsolete as well as largely inefficient and wasteful, and it makes virtually all LSPs highly vulnerable to disintermediation and disruption.

Technology might help LSPs differentiate and diversify, but it is deified; industry players seek a sort of endorsement in technology. This is mostly due to ignorance and arrogance together. It is no coincidence that the translation industry can be seen as a perfect implementation of Neil Postman’s technopoly.

In this respect, consolidation could help strengthen while streamlining processes and focus on differentiation and diversification strategies. This is why merging is more than joining forces. Any consolidation requires deep BPR, and this should start way before the actual merging process begins.

Larger ‘catchment areas’ and resource availability following merging will allow the resulting company to identify the most profitable markets and focus its marketing and sales efforts, while cutting redundant staff and redeploying workforces based on the new mission, the new processes, and the new goals. A first step might be shifting from virtually distinct and separate but actually blending when not overlapping functions to a service- and goal-oriented organization. To accommodate the shift towards vertical markets, a paradigm change is needed: Translation project management, especially in the industry’s typical file-sorting fashion, is no rocket science. Almost no hard skills are required while the most appreciated soft skills are used for account management. This might become a crucial task in any vertical-oriented LSP. In fact, retaining a (supposedly) loyal client requires a deep knowledge of its industry, its organization, its operations, and even its customers. Also, many of the trivial tasks usually performed by project managers will soon be entirely performed by data-driven platforms. The core business of any LSP will therefore be the service, which will no longer be in pooling and coordinating recruits but in listening to customers, interpreting their needs and then selecting the best technology and the right people to fulfill them. In this respect, active vendor management and data management will be essential.

Data as assets

Only a few years ago, at industry events, many speakers insisted that LSPs should consider glossaries and translation memories as assets. They usually received warm applause from the floor, even though they all knew for sure that, in real life, it was rare that glossaries and translation memories received the attention and care usually reserved to assets. In practice, data was used as a negotiation lever and nothing else. Essentially things have not changed since then.

At this point, an obvious and basic question arises: what would the budget value be for these supposed assets? Assets determine a company’s solvency. To be solvent, what you own must be worth more than your debts: When you are insolvent, you most likely go bankrupt.

In You Are Not a Gadget (2010), Jaron Lanier warned that if you aren’t paying for a product then you are the product. However, people are ready to sell their personal data to any monster-company that will exploit it more daringly than we would ever think. This should not mean that although this data is gold for such companies, it is nothing for its owners. The profit that can be generated on this data is not apparent and the perceived benefits that any user is supposed to receive for free outbalance any exploitation.

This is why, periodically, in spite of any previous failure, the idea of a translation data marketplace resurfaces. However, inflating the presumed value of language data led its owners to be reluctant to sell it or even to exchange it, if not in the face of tangible benefits. Unfortunately, no one seems capable of offering any of these benefits, so far.

In the digital space, in which perfect, instantaneous copying is possible, many traditionally rivalrous objects become non-rivalrous. Non-rivalrous objects are objects that can be given to or taken by another without the original copy being lost. Knowledge and many knowledge-related digital items are like this and are treated as though they were rivalrous so that they are compatible with our systems of finance. Unfortunately, unique digital knowledge is a flawed concept as non-rivalrous digital objects can be copied ad infinitum. And this is the base to the hostility to exchanging any form of knowledge for free, because ‘authors’ claim an ownership right on it. This hostility is motivated by the fear of being deprived of it, even though anyone intimately knows that knowledge cannot be stolen.

In the end, problems in sharing data for domain customization might inhibit this market.

Indeed, blockchain might help here, at least in theory. One of the most obvious applications of blockchain technology is as a registry of IP rights to catalogue and store original works. Since ownership of data can be hard to prove, it can be hard for owners to see who is using it and for third parties to use it legitimately. The problem remains of providing evidence of creatorship, legitimate ownership, and provenance authentication. Anyone could upload any data and get a blockchain certificate without giving any evidence of its genuine ownership, but once the blockchain transaction is completed, the cryptographic fingerprint will be a proof of ownership, and it cannot be changed. The same will happen with the ensuing digital trail of records.

Also, because of the overheads involved in shuffling data between all participants, blockchains are less efficient than centralized databases, a problem that gets worse as the number of users rises. This is possibly why, according to Forrester Research, 90 percent of experiments will be wound down this year. According to a Gartner study, this is due to a significant disconnect between the hype and the reality, and only 8 percent of CIOs are going to plain any kind of active experimentation with blockchain in the short-term, with nearly 80 percent of them revealing no interest in the technology. One reason behind the delays is in the incompatibility of most blockchain software, so companies are worried about a possible vendor lock-in, and the experience with bitcoin proved effective but also extremely inefficient. Also, what about GDPR?

So, even when a blockchain might be a suitable tool, several problems still need to be solved, starting with the identification of a standard. In this case, the history of standards in the translation industry shows that the real toil would be in having everyone agree on even basic details such as who will be in charge, how the system will be built, how data formats will work and what happens if someone wants to leave. In this industry? Good luck with that!

In awe of MT

In brief, blockchain is not exactly the recipe for all the entrepreneurial, financial, technological and attitude delays affecting the industry. And with tech giants busting personal data every day without a shot, a data marketplace, given the general current state of language data, does not even seem to be the killer investment, albeit done with public money.

However, both efforts are to be appreciated if one considers that most supposedly prosperous translation professionals, after having been demonizing machine translation for years, are now most possibly using it, obviously through free online services. They are still in awe of it, of course, possibly scared to death more than ever, as the new ‘it-is-just-a-tool’ attitude shows.

At the same time, the same brave professionals obsessively recite that the translation industry has the power to lead people to erase the difference between human translations and machine translations in the minds of people. Of course, this is not 1984, the translation industry is not the government and Hélène Pielmeier’s post tells another story, but these people have erected fake-news propaganda as their creed and accurately picked bullshitters for leaders. They pretend to ignore that FAANGs are not the translation industry. Or maybe this is just one of the many things that must be unclear to people who pretend to have clear ideas and very strong opinions about everything, including on why machine translation is not an option to supplement the many other resources they should use.

Indeed, in the translation technopoly, many smaller LSPs are looking into including MT in their offering, in a desperate effort to differentiate. They seem to ignore that technology always makes less progress than you expect in the short term and much more in the long term. And that in the long run, we are all dead.

One wonders why few seem to see that MT companies are all in troubles, gone or acquired or surviving thanks to generous public funding, following the reviled paradigm of The Entrepreneurial State so brilliantly described by Mariana Mazzucato. Maybe also a data marketplace is viable—not necessarily successful— only via public funding.

MT will be ever more critical while still computationally demanding and resource intensive, requiring skilled engineers and data experts, thus increasingly cutting out less equipped organizations that will have to rely on bigger suppliers. Their first line of defense, but definitely not assets, will be their long-time data, which must be painstakingly cared though. On the other hand, translators will be more and more vulnerable and have to look for other services to differentiate their offering.

In any case, crowdsourcing won’t last. In less than three years the gig economy will be still profitable only for early starters that have differentiated their models in the meanwhile (like Uber). The kind of disintermediation brought by the platform economy boom is not going to impact on large contracts, generally on B2B transactions. Real disintermediation in this case will happen through the platforms implemented and run by those companies that would be able to attract and retain the best resources, and the skill shortage will become even more acute.

The Court has re-stated that the risk that workers who should be treated as employees may be improperly misclassified as independent contractors is significant considering the potentially substantial economic incentives that a business may have in mischaracterizing some workers as independent contractors. Such incentives include the unfair competitive advantage the business may obtain over competitors that properly classify similar workers as employees and that thereby assume the fiscal and other responsibilities and burdens that an employer owes to its employees.

This scenario typically applies to gig economy companies like Dynamex that, indeed, the Court has held as having misclassified its workers. The Court has also stated that work definition cannot be interpreted literally to encompass within the employee category the type of individual workers who have traditionally been viewed as genuine independent contractors who are working only in their own independent business.

In other words, Uber and the like can be a real menace for the system of rules, duties and rights that have been painstakingly developed for years to guarantee all the parties involved, thus the whole society.

Also, work is already defined and regulated in several countries, where the law sanctions as illegal the fake hiring of people who are formally self-employed contractors while being de facto employees, as having one client only for whom they work in his/her premises according to a specific working time. Any names coming to mind in the translation industry? Want a tip?

Not all the problems we face are new and require new solutions. Many come from the usual evils and we could just apply the existing solutions.

To identify and possibly solve problems that are really new, seriousness and competence are the first requisites. And both are still a rare commodity.